Overview

Dataset statistics

Number of variables15
Number of observations30000
Missing cells74980
Missing cells (%)16.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory37.5 MiB
Average record size in memory1.3 KiB

Variable types

Text10
Boolean2
Categorical3

Alerts

reviews_doRecommend is highly overall correlated with reviews_rating and 1 other fieldsHigh correlation
reviews_rating is highly overall correlated with reviews_doRecommendHigh correlation
reviews_userProvince is highly overall correlated with reviews_doRecommendHigh correlation
reviews_didPurchase is highly imbalanced (56.4%)Imbalance
reviews_doRecommend is highly imbalanced (68.7%)Imbalance
reviews_didPurchase has 14068 (46.9%) missing valuesMissing
reviews_doRecommend has 2570 (8.6%) missing valuesMissing
reviews_userCity has 28071 (93.6%) missing valuesMissing
reviews_userProvince has 29830 (99.4%) missing valuesMissing

Reproduction

Analysis started2024-06-23 10:21:44.642440
Analysis finished2024-06-23 10:21:46.382621
Duration1.74 second
Software versionydata-profiling v4.8.3
Download configurationconfig.json

Variables

id
Text

Distinct271
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.2 MiB
2024-06-23T22:21:46.463544image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters600000
Distinct characters64
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique49 ?
Unique (%)0.2%

Sample

1st rowAV13O1A8GV-KLJ3akUyj
2nd rowAV14LG0R-jtxr-f38QfS
3rd rowAV14LG0R-jtxr-f38QfS
4th rowAV16khLE-jtxr-f38VFn
5th rowAV16khLE-jtxr-f38VFn
ValueCountFrequency (%)
avpf3vofilapnd_xjpun 8545
28.5%
avpfpaoqljejml435xk9 3325
 
11.1%
avpfjp1c1cnluz0-e3xy 2039
 
6.8%
avpfw8y_ljejml437ysw 1186
 
4.0%
avpfrth1ilapnd_xyic2 1143
 
3.8%
avpf63ajljejml43f__q 873
 
2.9%
avpf0eb2ljejml43evst 845
 
2.8%
avpe41tqilapnd_xqh3d 757
 
2.5%
avpfm8yiljejml43ayyu 693
 
2.3%
avpf2tw1ilapnd_xjflc 672
 
2.2%
Other values (261) 9922
33.1%
2024-06-23T22:21:46.600644image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 45592
 
7.6%
V 41098
 
6.8%
p 38641
 
6.4%
f 35966
 
6.0%
n 29274
 
4.9%
3 24175
 
4.0%
J 23350
 
3.9%
l 21320
 
3.6%
L 20965
 
3.5%
P 20151
 
3.4%
Other values (54) 299468
49.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 600000
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
A 45592
 
7.6%
V 41098
 
6.8%
p 38641
 
6.4%
f 35966
 
6.0%
n 29274
 
4.9%
3 24175
 
4.0%
J 23350
 
3.9%
l 21320
 
3.6%
L 20965
 
3.5%
P 20151
 
3.4%
Other values (54) 299468
49.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 600000
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
A 45592
 
7.6%
V 41098
 
6.8%
p 38641
 
6.4%
f 35966
 
6.0%
n 29274
 
4.9%
3 24175
 
4.0%
J 23350
 
3.9%
l 21320
 
3.6%
L 20965
 
3.5%
P 20151
 
3.4%
Other values (54) 299468
49.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 600000
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
A 45592
 
7.6%
V 41098
 
6.8%
p 38641
 
6.4%
f 35966
 
6.0%
n 29274
 
4.9%
3 24175
 
4.0%
J 23350
 
3.9%
l 21320
 
3.6%
L 20965
 
3.5%
P 20151
 
3.4%
Other values (54) 299468
49.9%

brand
Text

Distinct214
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
2024-06-23T22:21:46.733252image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/

Length

Max length30
Median length28
Mean length9.3696667
Min length3

Characters and Unicode

Total characters281090
Distinct characters58
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)0.1%

Sample

1st rowUniversal Music
2nd rowLundberg
3rd rowLundberg
4th rowK-Y
5th rowK-Y
ValueCountFrequency (%)
clorox 10585
22.9%
home 4058
 
8.8%
warner 3994
 
8.6%
video 3993
 
8.6%
l'oreal 1310
 
2.8%
paris 1310
 
2.8%
disney 1200
 
2.6%
sony 891
 
1.9%
fox 887
 
1.9%
burt's 881
 
1.9%
Other values (293) 17185
37.1%
2024-06-23T22:21:46.903735image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 36010
 
12.8%
r 30031
 
10.7%
e 27968
 
9.9%
16294
 
5.8%
l 15720
 
5.6%
a 13850
 
4.9%
i 12814
 
4.6%
n 12812
 
4.6%
x 12777
 
4.5%
C 12024
 
4.3%
Other values (48) 90790
32.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 281090
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o 36010
 
12.8%
r 30031
 
10.7%
e 27968
 
9.9%
16294
 
5.8%
l 15720
 
5.6%
a 13850
 
4.9%
i 12814
 
4.6%
n 12812
 
4.6%
x 12777
 
4.5%
C 12024
 
4.3%
Other values (48) 90790
32.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 281090
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o 36010
 
12.8%
r 30031
 
10.7%
e 27968
 
9.9%
16294
 
5.8%
l 15720
 
5.6%
a 13850
 
4.9%
i 12814
 
4.6%
n 12812
 
4.6%
x 12777
 
4.5%
C 12024
 
4.3%
Other values (48) 90790
32.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 281090
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o 36010
 
12.8%
r 30031
 
10.7%
e 27968
 
9.9%
16294
 
5.8%
l 15720
 
5.6%
a 13850
 
4.9%
i 12814
 
4.6%
n 12812
 
4.6%
x 12777
 
4.5%
C 12024
 
4.3%
Other values (48) 90790
32.3%
Distinct270
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size9.1 MiB
2024-06-23T22:21:46.995004image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/

Length

Max length518
Median length374
Mean length262.18357
Min length42

Characters and Unicode

Total characters7865507
Distinct characters71
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique48 ?
Unique (%)0.2%

Sample

1st rowMovies, Music & Books,Music,R&b,Movies & TV,Movie Bundles & Collections,CDs & Vinyl,Rap & Hip-Hop,Bass,Music on CD or Vinyl,Rap,Hip-Hop,Mainstream Rap,Pop Rap
2nd rowFood,Packaged Foods,Snacks,Crackers,Snacks, Cookies & Chips,Rice Cakes,Cakes
3rd rowFood,Packaged Foods,Snacks,Crackers,Snacks, Cookies & Chips,Rice Cakes,Cakes
4th rowPersonal Care,Medicine Cabinet,Lubricant/Spermicide,Health,Sexual Wellness,Lubricants
5th rowPersonal Care,Medicine Cabinet,Lubricant/Spermicide,Health,Sexual Wellness,Lubricants
ValueCountFrequency (%)
153588
 
21.5%
to 14333
 
2.0%
and 13005
 
1.8%
movies 12608
 
1.8%
tv 12200
 
1.7%
household 11321
 
1.6%
household,household 11218
 
1.6%
supplies,household 11107
 
1.6%
storage 11077
 
1.6%
brands,home 11065
 
1.5%
Other values (1885) 452408
63.4%
2024-06-23T22:21:47.123600image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 721512
 
9.2%
689330
 
8.8%
s 606910
 
7.7%
o 539027
 
6.9%
a 470043
 
6.0%
, 464769
 
5.9%
i 410763
 
5.2%
n 410185
 
5.2%
l 397456
 
5.1%
r 380680
 
4.8%
Other values (61) 2774832
35.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 7865507
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 721512
 
9.2%
689330
 
8.8%
s 606910
 
7.7%
o 539027
 
6.9%
a 470043
 
6.0%
, 464769
 
5.9%
i 410763
 
5.2%
n 410185
 
5.2%
l 397456
 
5.1%
r 380680
 
4.8%
Other values (61) 2774832
35.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 7865507
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 721512
 
9.2%
689330
 
8.8%
s 606910
 
7.7%
o 539027
 
6.9%
a 470043
 
6.0%
, 464769
 
5.9%
i 410763
 
5.2%
n 410185
 
5.2%
l 397456
 
5.1%
r 380680
 
4.8%
Other values (61) 2774832
35.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 7865507
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 721512
 
9.2%
689330
 
8.8%
s 606910
 
7.7%
o 539027
 
6.9%
a 470043
 
6.0%
, 464769
 
5.9%
i 410763
 
5.2%
n 410185
 
5.2%
l 397456
 
5.1%
r 380680
 
4.8%
Other values (61) 2774832
35.3%
Distinct227
Distinct (%)0.8%
Missing141
Missing (%)0.5%
Memory size1.9 MiB
2024-06-23T22:21:47.248257image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/

Length

Max length36
Median length31
Mean length9.8143608
Min length3

Characters and Unicode

Total characters293047
Distinct characters65
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)0.1%

Sample

1st rowUniversal Music Group / Cash Money
2nd rowLundberg
3rd rowLundberg
4th rowK-Y
5th rowK-Y
ValueCountFrequency (%)
clorox 8546
 
19.0%
test 3325
 
7.4%
amazonus/cloo7 2039
 
4.5%
l'oreal 1254
 
2.8%
paris 1232
 
2.7%
disney 1173
 
2.6%
walt 1172
 
2.6%
fox 887
 
2.0%
century 887
 
2.0%
bees 881
 
2.0%
Other values (343) 23491
52.3%
2024-06-23T22:21:47.417581image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 29131
 
9.9%
e 22638
 
7.7%
r 21623
 
7.4%
s 15641
 
5.3%
t 15583
 
5.3%
15028
 
5.1%
C 14522
 
5.0%
l 13884
 
4.7%
n 13500
 
4.6%
a 13148
 
4.5%
Other values (55) 118349
40.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 293047
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o 29131
 
9.9%
e 22638
 
7.7%
r 21623
 
7.4%
s 15641
 
5.3%
t 15583
 
5.3%
15028
 
5.1%
C 14522
 
5.0%
l 13884
 
4.7%
n 13500
 
4.6%
a 13148
 
4.5%
Other values (55) 118349
40.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 293047
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o 29131
 
9.9%
e 22638
 
7.7%
r 21623
 
7.4%
s 15641
 
5.3%
t 15583
 
5.3%
15028
 
5.1%
C 14522
 
5.0%
l 13884
 
4.7%
n 13500
 
4.6%
a 13148
 
4.5%
Other values (55) 118349
40.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 293047
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o 29131
 
9.9%
e 22638
 
7.7%
r 21623
 
7.4%
s 15641
 
5.3%
t 15583
 
5.3%
15028
 
5.1%
C 14522
 
5.0%
l 13884
 
4.7%
n 13500
 
4.6%
a 13148
 
4.5%
Other values (55) 118349
40.4%

name
Text

Distinct271
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size3.2 MiB
2024-06-23T22:21:47.569462image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/

Length

Max length103
Median length93
Mean length53.391367
Min length13

Characters and Unicode

Total characters1601741
Distinct characters76
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique49 ?
Unique (%)0.2%

Sample

1st rowPink Friday: Roman Reloaded Re-Up (w/dvd)
2nd rowLundberg Organic Cinnamon Toast Rice Cakes
3rd rowLundberg Organic Cinnamon Toast Rice Cakes
4th rowK-Y Love Sensuality Pleasure Gel
5th rowK-Y Love Sensuality Pleasure Gel
ValueCountFrequency (%)
clorox 10585
 
4.5%
disinfecting 10584
 
4.5%
total 8917
 
3.8%
pack 8567
 
3.7%
wipes 8561
 
3.7%
ct 8546
 
3.7%
value 8545
 
3.6%
scented 8545
 
3.6%
150 8545
 
3.6%
digital 6140
 
2.6%
Other values (1238) 146589
62.6%
2024-06-23T22:21:47.771635image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
204124
 
12.7%
e 125397
 
7.8%
i 110828
 
6.9%
a 90397
 
5.6%
l 88982
 
5.6%
t 86526
 
5.4%
o 79931
 
5.0%
n 73270
 
4.6%
d 59106
 
3.7%
r 57085
 
3.6%
Other values (66) 626095
39.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1601741
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
204124
 
12.7%
e 125397
 
7.8%
i 110828
 
6.9%
a 90397
 
5.6%
l 88982
 
5.6%
t 86526
 
5.4%
o 79931
 
5.0%
n 73270
 
4.6%
d 59106
 
3.7%
r 57085
 
3.6%
Other values (66) 626095
39.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1601741
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
204124
 
12.7%
e 125397
 
7.8%
i 110828
 
6.9%
a 90397
 
5.6%
l 88982
 
5.6%
t 86526
 
5.4%
o 79931
 
5.0%
n 73270
 
4.6%
d 59106
 
3.7%
r 57085
 
3.6%
Other values (66) 626095
39.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1601741
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
204124
 
12.7%
e 125397
 
7.8%
i 110828
 
6.9%
a 90397
 
5.6%
l 88982
 
5.6%
t 86526
 
5.4%
o 79931
 
5.0%
n 73270
 
4.6%
d 59106
 
3.7%
r 57085
 
3.6%
Other values (66) 626095
39.1%
Distinct6857
Distinct (%)22.9%
Missing46
Missing (%)0.2%
Memory size2.3 MiB
2024-06-23T22:21:47.879313image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/

Length

Max length50
Median length24
Mean length23.914669
Min length20

Characters and Unicode

Total characters716340
Distinct characters33
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4798 ?
Unique (%)16.0%

Sample

1st row2012-11-30T06:21:45.000Z
2nd row2017-07-09T00:00:00.000Z
3rd row2017-07-09T00:00:00.000Z
4th row2016-01-06T00:00:00.000Z
5th row2016-12-21T00:00:00.000Z
ValueCountFrequency (%)
2012-01-26t00:00:00.000z 1041
 
3.5%
2014-12-03t00:00:00.000z 524
 
1.7%
2014-09-19t00:00:00.000z 406
 
1.4%
2014-12-05t00:00:00.000z 345
 
1.1%
2014-12-04t00:00:00.000z 301
 
1.0%
2012-01-27t00:00:00.000z 300
 
1.0%
2014-11-07t00:00:00.000z 289
 
1.0%
2012-01-28t00:00:00.000z 278
 
0.9%
2014-12-27t00:00:00.000z 232
 
0.8%
2014-12-06t00:00:00.000z 208
 
0.7%
Other values (6854) 26086
86.9%
2024-06-23T22:21:48.016047image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 313683
43.8%
1 64334
 
9.0%
- 59892
 
8.4%
: 59892
 
8.4%
2 59753
 
8.3%
T 29946
 
4.2%
Z 29946
 
4.2%
. 29263
 
4.1%
4 14752
 
2.1%
5 12918
 
1.8%
Other values (23) 41961
 
5.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 716340
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 313683
43.8%
1 64334
 
9.0%
- 59892
 
8.4%
: 59892
 
8.4%
2 59753
 
8.3%
T 29946
 
4.2%
Z 29946
 
4.2%
. 29263
 
4.1%
4 14752
 
2.1%
5 12918
 
1.8%
Other values (23) 41961
 
5.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 716340
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 313683
43.8%
1 64334
 
9.0%
- 59892
 
8.4%
: 59892
 
8.4%
2 59753
 
8.3%
T 29946
 
4.2%
Z 29946
 
4.2%
. 29263
 
4.1%
4 14752
 
2.1%
5 12918
 
1.8%
Other values (23) 41961
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 716340
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 313683
43.8%
1 64334
 
9.0%
- 59892
 
8.4%
: 59892
 
8.4%
2 59753
 
8.3%
T 29946
 
4.2%
Z 29946
 
4.2%
. 29263
 
4.1%
4 14752
 
2.1%
5 12918
 
1.8%
Other values (23) 41961
 
5.9%

reviews_didPurchase
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing14068
Missing (%)46.9%
Memory size999.9 KiB
False
14498 
True
 
1434
(Missing)
14068 
ValueCountFrequency (%)
False 14498
48.3%
True 1434
 
4.8%
(Missing) 14068
46.9%
2024-06-23T22:21:48.076140image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/

reviews_doRecommend
Boolean

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing2570
Missing (%)8.6%
Memory size1.0 MiB
True
25880 
False
 
1550
(Missing)
 
2570
ValueCountFrequency (%)
True 25880
86.3%
False 1550
 
5.2%
(Missing) 2570
 
8.6%
2024-06-23T22:21:48.103113image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/

reviews_rating
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.7 MiB
5
20831 
4
6020 
1
 
1384
3
 
1345
2
 
420

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters30000
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5
2nd row5
3rd row5
4th row1
5th row1

Common Values

ValueCountFrequency (%)
5 20831
69.4%
4 6020
 
20.1%
1 1384
 
4.6%
3 1345
 
4.5%
2 420
 
1.4%

Length

2024-06-23T22:21:48.126818image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-06-23T22:21:48.160434image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
ValueCountFrequency (%)
5 20831
69.4%
4 6020
 
20.1%
1 1384
 
4.6%
3 1345
 
4.5%
2 420
 
1.4%

Most occurring characters

ValueCountFrequency (%)
5 20831
69.4%
4 6020
 
20.1%
1 1384
 
4.6%
3 1345
 
4.5%
2 420
 
1.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 30000
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
5 20831
69.4%
4 6020
 
20.1%
1 1384
 
4.6%
3 1345
 
4.5%
2 420
 
1.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 30000
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
5 20831
69.4%
4 6020
 
20.1%
1 1384
 
4.6%
3 1345
 
4.5%
2 420
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 30000
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
5 20831
69.4%
4 6020
 
20.1%
1 1384
 
4.6%
3 1345
 
4.5%
2 420
 
1.4%
Distinct27282
Distinct (%)90.9%
Missing0
Missing (%)0.0%
Memory size6.9 MiB
2024-06-23T22:21:48.264239image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/

Length

Max length5865
Median length1257
Mean length183.05697
Min length2

Characters and Unicode

Total characters5491709
Distinct characters94
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24711 ?
Unique (%)82.4%

Sample

1st rowi love this album. it's very good. more to the hip hop side than her current pop sound.. SO HYPE! i listen to this everyday at the gym! i give it 5star rating all the way. her metaphors are just crazy.
2nd rowGood flavor. This review was collected as part of a promotion.
3rd rowGood flavor.
4th rowI read through the reviews on here before looking in to buying one of the couples lubricants, and was ultimately disappointed that it didn't even live up to the reviews I had read. For starters, neither my boyfriend nor I could notice any sort of enhanced or 'captivating' sensation. What we did notice, however, was the messy consistency that was reminiscent of a more liquid-y vaseline. It was difficult to clean up, and was not a pleasant, especially since it lacked the 'captivating' sensation we had both been expecting. I'm disappointed that I paid as much as I did for a lube that I won't use again, when I could just use their normal personal lubricant for 1) less money and 2) less mess.
5th rowMy husband bought this gel for us. The gel caused irritation and it felt like it was burning my skin. I wouldn't recommend this gel.
ValueCountFrequency (%)
the 42938
 
4.2%
i 37866
 
3.7%
and 32804
 
3.2%
a 29963
 
2.9%
this 25934
 
2.5%
it 23211
 
2.3%
to 23140
 
2.2%
of 21078
 
2.0%
my 17191
 
1.7%
was 15854
 
1.5%
Other values (21942) 761595
73.8%
2024-06-23T22:21:48.430854image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1001591
18.2%
e 507270
 
9.2%
t 372623
 
6.8%
o 352362
 
6.4%
a 328509
 
6.0%
i 290020
 
5.3%
s 284155
 
5.2%
n 250464
 
4.6%
r 240567
 
4.4%
h 200231
 
3.6%
Other values (84) 1663917
30.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5491709
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1001591
18.2%
e 507270
 
9.2%
t 372623
 
6.8%
o 352362
 
6.4%
a 328509
 
6.0%
i 290020
 
5.3%
s 284155
 
5.2%
n 250464
 
4.6%
r 240567
 
4.4%
h 200231
 
3.6%
Other values (84) 1663917
30.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5491709
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1001591
18.2%
e 507270
 
9.2%
t 372623
 
6.8%
o 352362
 
6.4%
a 328509
 
6.0%
i 290020
 
5.3%
s 284155
 
5.2%
n 250464
 
4.6%
r 240567
 
4.4%
h 200231
 
3.6%
Other values (84) 1663917
30.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5491709
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1001591
18.2%
e 507270
 
9.2%
t 372623
 
6.8%
o 352362
 
6.4%
a 328509
 
6.0%
i 290020
 
5.3%
s 284155
 
5.2%
n 250464
 
4.6%
r 240567
 
4.4%
h 200231
 
3.6%
Other values (84) 1663917
30.3%
Distinct18535
Distinct (%)62.2%
Missing190
Missing (%)0.6%
Memory size2.1 MiB
2024-06-23T22:21:48.555241image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/

Length

Max length180
Median length104
Mean length18.096444
Min length1

Characters and Unicode

Total characters539455
Distinct characters90
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16145 ?
Unique (%)54.2%

Sample

1st rowJust Awesome
2nd rowGood
3rd rowGood
4th rowDisappointed
5th rowIrritation
ValueCountFrequency (%)
great 6103
 
6.4%
movie 3168
 
3.3%
product 3147
 
3.3%
love 2926
 
3.1%
the 2712
 
2.8%
good 2201
 
2.3%
this 1756
 
1.8%
wipes 1709
 
1.8%
for 1688
 
1.8%
clorox 1631
 
1.7%
Other values (5733) 68509
71.7%
2024-06-23T22:21:48.805058image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
65745
 
12.2%
e 54783
 
10.2%
o 39514
 
7.3%
t 33636
 
6.2%
r 28581
 
5.3%
i 28533
 
5.3%
a 27903
 
5.2%
s 24564
 
4.6%
n 20992
 
3.9%
l 19697
 
3.7%
Other values (80) 195507
36.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 539455
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
65745
 
12.2%
e 54783
 
10.2%
o 39514
 
7.3%
t 33636
 
6.2%
r 28581
 
5.3%
i 28533
 
5.3%
a 27903
 
5.2%
s 24564
 
4.6%
n 20992
 
3.9%
l 19697
 
3.7%
Other values (80) 195507
36.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 539455
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
65745
 
12.2%
e 54783
 
10.2%
o 39514
 
7.3%
t 33636
 
6.2%
r 28581
 
5.3%
i 28533
 
5.3%
a 27903
 
5.2%
s 24564
 
4.6%
n 20992
 
3.9%
l 19697
 
3.7%
Other values (80) 195507
36.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 539455
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
65745
 
12.2%
e 54783
 
10.2%
o 39514
 
7.3%
t 33636
 
6.2%
r 28581
 
5.3%
i 28533
 
5.3%
a 27903
 
5.2%
s 24564
 
4.6%
n 20992
 
3.9%
l 19697
 
3.7%
Other values (80) 195507
36.2%

reviews_userCity
Text

MISSING 

Distinct977
Distinct (%)50.6%
Missing28071
Missing (%)93.6%
Memory size1001.0 KiB
2024-06-23T22:21:48.922534image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/

Length

Max length40
Median length22
Mean length8.6360809
Min length2

Characters and Unicode

Total characters16659
Distinct characters55
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique705 ?
Unique (%)36.5%

Sample

1st rowLos Angeles
2nd rowRohnert Park
3rd rowBrooklyn
4th rowBrooklyn
5th rowHouston
ValueCountFrequency (%)
new 51
 
2.1%
san 47
 
2.0%
city 40
 
1.7%
chicago 34
 
1.4%
houston 32
 
1.3%
york 31
 
1.3%
los 26
 
1.1%
angeles 26
 
1.1%
atlanta 23
 
1.0%
boston 22
 
0.9%
Other values (1000) 2062
86.1%
2024-06-23T22:21:49.079164image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 1544
 
9.3%
e 1402
 
8.4%
o 1337
 
8.0%
n 1300
 
7.8%
i 1126
 
6.8%
l 1099
 
6.6%
r 937
 
5.6%
t 894
 
5.4%
s 789
 
4.7%
465
 
2.8%
Other values (45) 5766
34.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 16659
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 1544
 
9.3%
e 1402
 
8.4%
o 1337
 
8.0%
n 1300
 
7.8%
i 1126
 
6.8%
l 1099
 
6.6%
r 937
 
5.6%
t 894
 
5.4%
s 789
 
4.7%
465
 
2.8%
Other values (45) 5766
34.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 16659
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 1544
 
9.3%
e 1402
 
8.4%
o 1337
 
8.0%
n 1300
 
7.8%
i 1126
 
6.8%
l 1099
 
6.6%
r 937
 
5.6%
t 894
 
5.4%
s 789
 
4.7%
465
 
2.8%
Other values (45) 5766
34.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 16659
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 1544
 
9.3%
e 1402
 
8.4%
o 1337
 
8.0%
n 1300
 
7.8%
i 1126
 
6.8%
l 1099
 
6.6%
r 937
 
5.6%
t 894
 
5.4%
s 789
 
4.7%
465
 
2.8%
Other values (45) 5766
34.6%

reviews_userProvince
Categorical

HIGH CORRELATION  MISSING 

Distinct42
Distinct (%)24.7%
Missing29830
Missing (%)99.4%
Memory size1.8 MiB
CA
19 
TX
16 
FL
15 
OH
15 
NJ
10 
Other values (37)
95 

Length

Max length10
Median length2
Mean length2.0941176
Min length2

Characters and Unicode

Total characters356
Distinct characters36
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)8.2%

Sample

1st rowMI
2nd rowTX
3rd rowTX
4th rowME
5th rowOH

Common Values

ValueCountFrequency (%)
CA 19
 
0.1%
TX 16
 
0.1%
FL 15
 
0.1%
OH 15
 
0.1%
NJ 10
 
< 0.1%
MI 8
 
< 0.1%
IN 5
 
< 0.1%
NY 5
 
< 0.1%
AZ 5
 
< 0.1%
WA 4
 
< 0.1%
Other values (32) 68
 
0.2%
(Missing) 29830
99.4%

Length

2024-06-23T22:21:49.131975image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
ca 19
 
11.2%
tx 16
 
9.4%
fl 15
 
8.8%
oh 15
 
8.8%
nj 10
 
5.9%
mi 8
 
4.7%
in 5
 
2.9%
ny 5
 
2.9%
az 5
 
2.9%
tn 4
 
2.4%
Other values (32) 68
40.0%

Most occurring characters

ValueCountFrequency (%)
A 49
13.8%
N 33
 
9.3%
C 28
 
7.9%
L 25
 
7.0%
O 24
 
6.7%
I 24
 
6.7%
T 23
 
6.5%
M 20
 
5.6%
H 18
 
5.1%
X 16
 
4.5%
Other values (26) 96
27.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 356
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
A 49
13.8%
N 33
 
9.3%
C 28
 
7.9%
L 25
 
7.0%
O 24
 
6.7%
I 24
 
6.7%
T 23
 
6.5%
M 20
 
5.6%
H 18
 
5.1%
X 16
 
4.5%
Other values (26) 96
27.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 356
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
A 49
13.8%
N 33
 
9.3%
C 28
 
7.9%
L 25
 
7.0%
O 24
 
6.7%
I 24
 
6.7%
T 23
 
6.5%
M 20
 
5.6%
H 18
 
5.1%
X 16
 
4.5%
Other values (26) 96
27.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 356
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
A 49
13.8%
N 33
 
9.3%
C 28
 
7.9%
L 25
 
7.0%
O 24
 
6.7%
I 24
 
6.7%
T 23
 
6.5%
M 20
 
5.6%
H 18
 
5.1%
X 16
 
4.5%
Other values (26) 96
27.0%
Distinct24914
Distinct (%)83.2%
Missing63
Missing (%)0.2%
Memory size1.9 MiB
2024-06-23T22:21:49.265774image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/

Length

Max length59
Median length34
Mean length8.0268898
Min length1

Characters and Unicode

Total characters240301
Distinct characters49
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21304 ?
Unique (%)71.2%

Sample

1st rowjoshua
2nd rowdorothy w
3rd rowdorothy w
4th rowrebecca
5th rowwalker557
ValueCountFrequency (%)
the 62
 
0.2%
customer 56
 
0.2%
mike 43
 
0.1%
byamazon 43
 
0.1%
chris 33
 
0.1%
m 26
 
0.1%
b 23
 
0.1%
lisa 20
 
0.1%
d 20
 
0.1%
a 20
 
0.1%
Other values (25015) 30803
98.9%
2024-06-23T22:21:49.462364image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 21155
 
8.8%
e 21024
 
8.7%
i 13809
 
5.7%
r 13783
 
5.7%
n 13493
 
5.6%
o 12621
 
5.3%
s 12192
 
5.1%
l 11852
 
4.9%
m 10973
 
4.6%
t 9900
 
4.1%
Other values (39) 99499
41.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 240301
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 21155
 
8.8%
e 21024
 
8.7%
i 13809
 
5.7%
r 13783
 
5.7%
n 13493
 
5.6%
o 12621
 
5.3%
s 12192
 
5.1%
l 11852
 
4.9%
m 10973
 
4.6%
t 9900
 
4.1%
Other values (39) 99499
41.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 240301
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 21155
 
8.8%
e 21024
 
8.7%
i 13809
 
5.7%
r 13783
 
5.7%
n 13493
 
5.6%
o 12621
 
5.3%
s 12192
 
5.1%
l 11852
 
4.9%
m 10973
 
4.6%
t 9900
 
4.1%
Other values (39) 99499
41.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 240301
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 21155
 
8.8%
e 21024
 
8.7%
i 13809
 
5.7%
r 13783
 
5.7%
n 13493
 
5.6%
o 12621
 
5.3%
s 12192
 
5.1%
l 11852
 
4.9%
m 10973
 
4.6%
t 9900
 
4.1%
Other values (39) 99499
41.4%

user_sentiment
Categorical

Distinct2
Distinct (%)< 0.1%
Missing1
Missing (%)< 0.1%
Memory size1.9 MiB
Positive
26632 
Negative
3367 

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters239992
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPositive
2nd rowPositive
3rd rowPositive
4th rowNegative
5th rowNegative

Common Values

ValueCountFrequency (%)
Positive 26632
88.8%
Negative 3367
 
11.2%
(Missing) 1
 
< 0.1%

Length

2024-06-23T22:21:49.526446image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-06-23T22:21:49.556883image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
ValueCountFrequency (%)
positive 26632
88.8%
negative 3367
 
11.2%

Most occurring characters

ValueCountFrequency (%)
i 56631
23.6%
e 33366
13.9%
t 29999
12.5%
v 29999
12.5%
P 26632
11.1%
o 26632
11.1%
s 26632
11.1%
N 3367
 
1.4%
g 3367
 
1.4%
a 3367
 
1.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 239992
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i 56631
23.6%
e 33366
13.9%
t 29999
12.5%
v 29999
12.5%
P 26632
11.1%
o 26632
11.1%
s 26632
11.1%
N 3367
 
1.4%
g 3367
 
1.4%
a 3367
 
1.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 239992
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i 56631
23.6%
e 33366
13.9%
t 29999
12.5%
v 29999
12.5%
P 26632
11.1%
o 26632
11.1%
s 26632
11.1%
N 3367
 
1.4%
g 3367
 
1.4%
a 3367
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 239992
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 56631
23.6%
e 33366
13.9%
t 29999
12.5%
v 29999
12.5%
P 26632
11.1%
o 26632
11.1%
s 26632
11.1%
N 3367
 
1.4%
g 3367
 
1.4%
a 3367
 
1.4%

Correlations

2024-06-23T22:21:49.579787image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
reviews_didPurchasereviews_doRecommendreviews_ratingreviews_userProvinceuser_sentiment
reviews_didPurchase1.0000.0000.0540.0000.043
reviews_doRecommend0.0001.0000.8340.8060.199
reviews_rating0.0540.8341.0000.1230.244
reviews_userProvince0.0000.8060.1231.0000.000
user_sentiment0.0430.1990.2440.0001.000

Missing values

2024-06-23T22:21:46.032164image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
A simple visualization of nullity by column.
2024-06-23T22:21:46.169054image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-06-23T22:21:46.308673image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

idbrandcategoriesmanufacturernamereviews_datereviews_didPurchasereviews_doRecommendreviews_ratingreviews_textreviews_titlereviews_userCityreviews_userProvincereviews_usernameuser_sentiment
0AV13O1A8GV-KLJ3akUyjUniversal MusicMovies, Music & Books,Music,R&b,Movies & TV,Movie Bundles & Collections,CDs & Vinyl,Rap & Hip-Hop,Bass,Music on CD or Vinyl,Rap,Hip-Hop,Mainstream Rap,Pop RapUniversal Music Group / Cash MoneyPink Friday: Roman Reloaded Re-Up (w/dvd)2012-11-30T06:21:45.000ZNaNNaN5i love this album. it's very good. more to the hip hop side than her current pop sound.. SO HYPE! i listen to this everyday at the gym! i give it 5star rating all the way. her metaphors are just crazy.Just AwesomeLos AngelesNaNjoshuaPositive
1AV14LG0R-jtxr-f38QfSLundbergFood,Packaged Foods,Snacks,Crackers,Snacks, Cookies & Chips,Rice Cakes,CakesLundbergLundberg Organic Cinnamon Toast Rice Cakes2017-07-09T00:00:00.000ZTrueNaN5Good flavor. This review was collected as part of a promotion.GoodNaNNaNdorothy wPositive
2AV14LG0R-jtxr-f38QfSLundbergFood,Packaged Foods,Snacks,Crackers,Snacks, Cookies & Chips,Rice Cakes,CakesLundbergLundberg Organic Cinnamon Toast Rice Cakes2017-07-09T00:00:00.000ZTrueNaN5Good flavor.GoodNaNNaNdorothy wPositive
3AV16khLE-jtxr-f38VFnK-YPersonal Care,Medicine Cabinet,Lubricant/Spermicide,Health,Sexual Wellness,LubricantsK-YK-Y Love Sensuality Pleasure Gel2016-01-06T00:00:00.000ZFalseFalse1I read through the reviews on here before looking in to buying one of the couples lubricants, and was ultimately disappointed that it didn't even live up to the reviews I had read. For starters, neither my boyfriend nor I could notice any sort of enhanced or 'captivating' sensation. What we did notice, however, was the messy consistency that was reminiscent of a more liquid-y vaseline. It was difficult to clean up, and was not a pleasant, especially since it lacked the 'captivating' sensation we had both been expecting. I'm disappointed that I paid as much as I did for a lube that I won't use again, when I could just use their normal personal lubricant for 1) less money and 2) less mess.DisappointedNaNNaNrebeccaNegative
4AV16khLE-jtxr-f38VFnK-YPersonal Care,Medicine Cabinet,Lubricant/Spermicide,Health,Sexual Wellness,LubricantsK-YK-Y Love Sensuality Pleasure Gel2016-12-21T00:00:00.000ZFalseFalse1My husband bought this gel for us. The gel caused irritation and it felt like it was burning my skin. I wouldn't recommend this gel.IrritationNaNNaNwalker557Negative
5AV16khLE-jtxr-f38VFnK-YPersonal Care,Medicine Cabinet,Lubricant/Spermicide,Health,Sexual Wellness,LubricantsK-YK-Y Love Sensuality Pleasure Gel2016-04-20T00:00:00.000ZFalseFalse1My boyfriend and I bought this to spice things up in the bedroom and we were both highly disappointed in this product. We bought this one because we absolutely love the ky yours and mine and we thought this would have a similar affect but it did absolutely nothing. Do not buy.Not worth itNaNNaNsamanthaNegative
6AV16khLE-jtxr-f38VFnK-YPersonal Care,Medicine Cabinet,Lubricant/Spermicide,Health,Sexual Wellness,LubricantsK-YK-Y Love Sensuality Pleasure Gel2016-02-08T00:00:00.000ZFalseFalse1Bought this earlier today and was excited to check it out. Based on the product description I was expecting something but it was just like the regular KY. We are fans of the his and hers so we just expected more and were left a little disappointed.DisappointingNaNNaNraeanneNegative
7AV16khLE-jtxr-f38VFnK-YPersonal Care,Medicine Cabinet,Lubricant/Spermicide,Health,Sexual Wellness,LubricantsK-YK-Y Love Sensuality Pleasure Gel2016-02-21T00:00:00.000ZFalseFalse1I bought this product for my husband and I to try and we were not impressed at all. There was no tingling or warming. It left us both very sticky. I have used KY products in the past (loved KY his and hers) but this one was disappointing.Not happy at allNaNNaNkimmieNegative
8AV16khLE-jtxr-f38VFnK-YPersonal Care,Medicine Cabinet,Lubricant/Spermicide,Health,Sexual Wellness,LubricantsK-YK-Y Love Sensuality Pleasure Gel2016-03-28T00:00:00.000ZFalseFalse1My husband and I bought this for some extra fun. We werevboth extremely disappointed. Especially for the price! Do not waste your money on this product. We felt nothing but a sticky mess from it.Very disappointingNaNNaNcassieNegative
9AV16khLE-jtxr-f38VFnK-YPersonal Care,Medicine Cabinet,Lubricant/Spermicide,Health,Sexual Wellness,LubricantsK-YK-Y Love Sensuality Pleasure Gel2016-03-21T00:00:00.000ZFalseFalse1Got as a surprise for my husband there is nothing special about it just a lube save the money and get plain KY if you just need a lube wish I could return it for a refundDon't buyNaNNaNmoore222Positive
idbrandcategoriesmanufacturernamereviews_datereviews_didPurchasereviews_doRecommendreviews_ratingreviews_textreviews_titlereviews_userCityreviews_userProvincereviews_usernameuser_sentiment
29990AVpfW8y_LJeJML437ySWL'oreal ParisBeauty,Hair Care,Shampoo & Conditioner,Holiday Shop,Christmas,Featured Brands,Health & Beauty,L'oreal,Personal Care,Hair Treatments,ConditionerL'oreal ParisL'or233al Paris Elvive Extraordinary Clay Rebalancing Conditioner - 12.6 Fl Oz2016-12-26T00:00:00.000ZFalseTrue5This whole set of these (mask, shampoo and conditioner) works lovely. My roots get oily quickly and with this, they didn't! The smells of the mask and shampoo are alright, but I think the conditioner smells AMAZING. Recommend for anyone with the same oily root/dry ends problem. *I had received these products free/complimentary for testing purposes. All opinions are my own.* This review was collected as part of a promotion.Smells Amazing!NaNNaNemily646Positive
29991AVpfW8y_LJeJML437ySWL'oreal ParisBeauty,Hair Care,Shampoo & Conditioner,Holiday Shop,Christmas,Featured Brands,Health & Beauty,L'oreal,Personal Care,Hair Treatments,ConditionerL'oreal ParisL'or233al Paris Elvive Extraordinary Clay Rebalancing Conditioner - 12.6 Fl Oz2017-01-07T00:00:00.000ZFalseTrue5Took the 48 hour hair challenge using the shampoo, conditioner and clay mask. this was the 1st time I've heard of using clay. It worked good. My hair was clean. It smells good. It lasted 48 hours without getting oily. Received these products free for testing purposes but all opinions are my own. This review was collected as part of a promotion.Great clay products!NaNNaNmeganjoywolfePositive
29992AVpfW8y_LJeJML437ySWL'oreal ParisBeauty,Hair Care,Shampoo & Conditioner,Holiday Shop,Christmas,Featured Brands,Health & Beauty,L'oreal,Personal Care,Hair Treatments,ConditionerL'oreal ParisL'or233al Paris Elvive Extraordinary Clay Rebalancing Conditioner - 12.6 Fl Oz2016-12-16T00:00:00.000ZFalseTrue5I absolutely love the smell of this product! I have fine hair that is oily at the roots but the ends are dry. This left my hair feeling soft, the ends are not dry, and I didn't have to wash my hair last night (which I have to usually wash my hair every night). I couldn't be happier with this product and will most definitely be purchasing it again. I received these products free/complimentary for testing purposes, but all opinions are your own. This review was collected as part of a promotion.Smells AmazingNaNNaNkjb2205Positive
29993AVpfW8y_LJeJML437ySWL'oreal ParisBeauty,Hair Care,Shampoo & Conditioner,Holiday Shop,Christmas,Featured Brands,Health & Beauty,L'oreal,Personal Care,Hair Treatments,ConditionerL'oreal ParisL'or233al Paris Elvive Extraordinary Clay Rebalancing Conditioner - 12.6 Fl Oz2017-01-23T00:00:00.000ZFalseTrue5I seriously was so surprised after my shower how soft and healthy my shaft and ends felt and looked! not to mention super soft!! i received this product free for my review. This review was collected as part of a promotion.Ends feel so soft!NaNNaNmaryyyyyalicePositive
29994AVpfW8y_LJeJML437ySWL'oreal ParisBeauty,Hair Care,Shampoo & Conditioner,Holiday Shop,Christmas,Featured Brands,Health & Beauty,L'oreal,Personal Care,Hair Treatments,ConditionerL'oreal ParisL'or233al Paris Elvive Extraordinary Clay Rebalancing Conditioner - 12.6 Fl Oz2017-01-14T00:00:00.000ZFalseTrue5I got to try this conditioner for free and boy am I glad I did! It's amazing. It leaves your hair so soft and manageable and smells even more amazing! I would recommend anyone who wants great feeling hair that's not oily or dry to give this a try, you won't be disappointed. This review was collected as part of a promotion.By far, my new favorite conditionerNaNNaNsmartthunnyPositive
29995AVpfW8y_LJeJML437ySWL'oreal ParisBeauty,Hair Care,Shampoo & Conditioner,Holiday Shop,Christmas,Featured Brands,Health & Beauty,L'oreal,Personal Care,Hair Treatments,ConditionerL'oreal ParisL'or233al Paris Elvive Extraordinary Clay Rebalancing Conditioner - 12.6 Fl Oz2017-01-23T00:00:00.000ZFalseTrue5I got this conditioner with Influenster to try it and im loving it so far, i have oily hair so i use it only in the ends of my hair and feels amazing, so soft and no mess!! This review was collected as part of a promotion.Softness!!NaNNaNlaurasnchzPositive
29996AVpfW8y_LJeJML437ySWL'oreal ParisBeauty,Hair Care,Shampoo & Conditioner,Holiday Shop,Christmas,Featured Brands,Health & Beauty,L'oreal,Personal Care,Hair Treatments,ConditionerL'oreal ParisL'or233al Paris Elvive Extraordinary Clay Rebalancing Conditioner - 12.6 Fl Oz2017-01-27T00:00:00.000ZFalseTrue5I love it , I received this for review purposes from influenster and it leaves my hair feeling fresh and smelling greatI love itNaNNaNscarlepadillaPositive
29997AVpfW8y_LJeJML437ySWL'oreal ParisBeauty,Hair Care,Shampoo & Conditioner,Holiday Shop,Christmas,Featured Brands,Health & Beauty,L'oreal,Personal Care,Hair Treatments,ConditionerL'oreal ParisL'or233al Paris Elvive Extraordinary Clay Rebalancing Conditioner - 12.6 Fl Oz2017-01-21T00:00:00.000ZFalseTrue5First of all I love the smell of this product. After you wash your hair it is so smooth and easy to brush! I did receive this product from influenster for testing purposes but all opinions ARE my own! This review was collected as part of a promotion.Hair is so smooth after useNaNNaNliviasuexoPositive
29998AVpfW8y_LJeJML437ySWL'oreal ParisBeauty,Hair Care,Shampoo & Conditioner,Holiday Shop,Christmas,Featured Brands,Health & Beauty,L'oreal,Personal Care,Hair Treatments,ConditionerL'oreal ParisL'or233al Paris Elvive Extraordinary Clay Rebalancing Conditioner - 12.6 Fl Oz2017-01-11T00:00:00.000ZFalseTrue5I received this through Influenster and will never go back to anything else! I normally don't use conditioner because my hair is so oily and fine. This does not make my hair feel heavy, and it doesn't get oily during the day! It really is fantastic and plan on buying it in the future! This review was collected as part of a promotion.Perfect for my oily hair!NaNNaNktreed95Positive
29999AVpfW8y_LJeJML437ySWL'oreal ParisBeauty,Hair Care,Shampoo & Conditioner,Holiday Shop,Christmas,Featured Brands,Health & Beauty,L'oreal,Personal Care,Hair Treatments,ConditionerL'oreal ParisL'or233al Paris Elvive Extraordinary Clay Rebalancing Conditioner - 12.6 Fl Oz2017-01-19T00:00:00.000ZFalseTrue5I received this product complimentary from influenster and it has really saved my hair. This product really gives the extra boost of health and strength to bring hair back to life. It hasn't helped my hair in so many ways. This review was collected as part of a promotion.Conditioned into healthyNaNNaNkcoopxoxoPositive